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2020 – today
- 2024
[c7]Marissa Radensky
:
Mixed-Initiative Methods for Co-Creation in Scientific Research. Creativity & Cognition 2024: 1-7- [i6]Marissa Radensky, Daniel S. Weld, Joseph Chee Chang, Pao Siangliulue, Jonathan Bragg:
Let's Get to the Point: LLM-Supported Planning, Drafting, and Revising of Research-Paper Blog Posts. CoRR abs/2406.10370 (2024) - [i5]Marissa Radensky, Simra Shahid, Raymond Fok, Pao Siangliulue, Tom Hope, Daniel S. Weld:
Scideator: Human-LLM Scientific Idea Generation Grounded in Research-Paper Facet Recombination. CoRR abs/2409.14634 (2024) - 2023
- [c6]Marissa Radensky, Julie Anne Séguin, Jang Soo Lim, Kristen Olson, Robert Geiger:
"I Think You Might Like This": Exploring Effects of Confidence Signal Patterns on Trust in and Reliance on Conversational Recommender Systems. FAccT 2023: 792-804 - 2022
- [c5]Marissa Radensky, Doug Downey, Kyle Lo, Zoran Popovic, Daniel S. Weld:
Exploring the Role of Local and Global Explanations in Recommender Systems. CHI Extended Abstracts 2022: 290:1-290:7 - [c4]Jason Portenoy, Marissa Radensky, Jevin D. West, Eric Horvitz, Daniel S. Weld, Tom Hope:
Bursting Scientific Filter Bubbles: Boosting Innovation via Novel Author Discovery. CHI 2022: 309:1-309:13 - [i4]Marissa Radensky, Dustin Burson, Rajya Bhaiya, Daniel S. Weld:
Exploring How Anomalous Model Input and Output Alerts Affect Decision-Making in Healthcare. CoRR abs/2204.13194 (2022) - 2021
- [i3]Jason Portenoy, Marissa Radensky, Jevin West, Eric Horvitz, Daniel S. Weld, Tom Hope:
Bridger: Toward Bursting Scientific Filter Bubbles and Boosting Innovation via Novel Author Discovery. CoRR abs/2108.05669 (2021) - [i2]Marissa Radensky, Doug Downey, Kyle Lo, Zoran Popovic, Daniel S. Weld:
Exploring The Role of Local and Global Explanations in Recommender Systems. CoRR abs/2109.13301 (2021)
2010 – 2019
- 2019
- [c3]Toby Jia-Jun Li, Marissa Radensky, Justin Jia, Kirielle Singarajah, Tom M. Mitchell, Brad A. Myers:
PUMICE: A Multi-Modal Agent that Learns Concepts and Conditionals from Natural Language and Demonstrations. UIST 2019: 577-589 - [i1]Toby Jia-Jun Li, Marissa Radensky, Justin Jia, Kirielle Singarajah, Tom M. Mitchell, Brad A. Myers:
PUMICE: A Multi-Modal Agent that Learns Concepts and Conditionals from Natural Language and Demonstrations. CoRR abs/1909.00031 (2019) - 2018
- [c2]Mary Beth Kery, Marissa Radensky, Mahima Arya, Bonnie E. John, Brad A. Myers:
The Story in the Notebook: Exploratory Data Science using a Literate Programming Tool. CHI 2018: 174 - [c1]Marissa Radensky, Toby Jia-Jun Li, Brad A. Myers:
How End Users Express Conditionals in Programming by Demonstration for Mobile Apps. VL/HCC 2018: 311-312
Coauthor Index
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